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Record W1987416257 · doi:10.1002/2014jc010193

Observations of wave shear stress on a steep beach

2014· article· en· W1987416257 on OpenAlexafffund
G. Wilson, Alex E. Hay, A. J. Bowen

Bibliographic record

VenueJournal of Geophysical Research Oceans · 2014
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicCoastal and Marine Dynamics
Canadian institutionsDalhousie University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsShear (geology)DissipationGeologyWave shoalingShear stressAiry wave theoryWavenumberBoundary layerScale (ratio)MechanicsGeotechnical engineeringBreaking wavePhysicsWave propagationOpticsMechanical waveStokes waveLongitudinal waveThermodynamics

Abstract

fetched live from OpenAlex

Observations are presented of the wave shear stress 〈u∼w∼〉 on a steeply sloping beach. Above the wave boundary layer (WBL), positive values of 〈u∼w∼〉 were observed and are attributed to a combination of both wave shoaling due to the large-scale bed slope, and dissipation due to wave breaking, in agreement with the wave theory of Zou et al. (2003). Within the WBL, observed vertical profiles of 〈u∼w∼〉 were also in good agreement with theory, in cases where the wave height was small. As wave heights increased, however, the WBL profile of 〈u∼w∼〉 generally did not agree with theory. Near-simultaneous rotary sonar observations of the bed suggest the disagreement with theory was due to the presence of orbital-scale ripples, which the present theory does not accommodate.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.060
GPT teacher head0.295
Teacher spread0.234 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations8
Published2014
Admission routes2
Has abstractyes

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